Closed circuit television, and other video surveillance methods are commonly used for crime control. Per http://www.privacy.org/pi/issues/cctv/, 225–450 million dollars “per year is now spent on a surveillance industry involving an estimated 300,000 cameras covering shopping areas, housing estates, car parks and public facilities in great many towns and cities.” Systems to enable such surveillance are commonly sold to security services, consumers and over the Internet. http://www.smarthome.com/secvidsur.html for example sells a variety of equipment for video surveillance.
These surveillance systems require active monitoring, and are generally viewed as potential privacy violations. Privacy concerns lead to the posting of surveillance policies in places such as locker rooms and dressing rooms.
In 1997, Defense Advanced Research Projects Agency (DARPA) Information Systems Office began a program to develop Video Surveillance and Monitoring (VSAM) technology. This technology is intended to alert an operator during an event in progress (such as a crime) in time to prevent the crime. The technology triggers an operator to view a video feed and take appropriate action. It does not protect privacy, and is triggered by observed action at one of the points of monitoring. (see http://www.cs.cmu.edu/˜vsam/vsamhome.html).
Another technology in this space is scene change detection. Scene change detection is used in the media industry as an aid to editing and indexing media. It accomplishes just what the name implies. Video is examined for significant differences on a “frame by frame” basis. When the differences meet criteria, a scene change is declared. These are used in the media industry to create storyboards of a video, to create indexes for media manipulation, and as an aid in editing, e.g. for example in creating a nightly news story. Scene change detection is taught by such patents as U.S. Pat. No. 6,101,222 and U.S. Pat. No. 5,099,322. Scene change detection is offered as part of content management systems by Virage (http://www.virage.com), and Bulldog (http://www.bulldog.com).
Audio change detection, determining where in an audio stream a particular loudness or frequency threshold has been reached can also be used to determine events of interest, such as a score in a football game, or a gunshot. See U.S. Pat. No. 6,163,510 to Lee et al.
Medical alert systems, comprising a pendant or other device, worn by the user allow an at-risk individual to signal to a distant system or person that an emergency has occurred. These have been popularized as “I've fallen and I can't get up” devices. Offered by companies such as Responselink, these systems include a wearable portion, power transformer, batteries, phone connection, and a monitoring service. The monitoring service, usually with a monthly fee, responds to alerts submitted by the user. Note that the user must have the ability to press the button and signal the alert for the alert to be sent. Injuries that involve rapid loss of consciousness may prevent the user from such signaling. Responselink information can be found at http://www.responselink.com
Periodic phone calls are also used to check on at-risk people. Relatives, friends or a paid service can call the individuals and ascertain from their responses whether or not they are OK.
Face recognition is a technology which can identify faces, and in many cases associate them with names in a database. Visionics (http://www.visionics.com) offers a product called FaceIt which “will automatically locate faces in complex scenes . . . ”
All these cited references are herein incorporated by reference in their entirety.